The Structure of m–Stable Sets and in Particular of the Set of Risk Neutral Measures

By Freddy Delbaen. 2006

212 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/52fb3c5be2e0a649db1d0236e20b2fd4d068aa36

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Citations in the corpus

Optimal Stopping for Dynamic Convex Risk Measures (2009, background): “The papers [6] and [14], on the other hand, considered continuous-time optimal stopping problems in which the essential infimum over the stopping times in (1.”
DYNAMIC INDIFFERENCE VALUATION VIA CONVEX RISK MEASURES (2007, background): “Similarly as in Theorems 12 and 16 in Delbaen (2006b), time-consistency can then be characterized as follows; see also Proposition 8 of DS. LEMMA 3.5.”
VALUATIONS AND DYNAMIC CONVEX RISK MEASURES (2007, methodology): “articularly Philippe Artzner, Alexander Cherny, Phil Dybvig, Marco Frittelli, Lars Hansen, and Jose Scheinkman; and two anonymous referees whose comments have resulted in numerous improvements. 3 See [2, 20, 13, 1, 21, 12, 11, 27, 14, 22, 24, 9] for one-period risk-measurement, [3] for the multiperi”
Optimal stopping for non-linear expectations—Part I (2011, unknown): “The stability is also referred to as “fork convexity” in stochastic control theory, “m-stability” in stochastic analysis or “rectangularity” in decision theory (see the introduction of [5,2] for details).”
Time-Inconsistency of VaR and Time-Consistent Alternatives (2007, unknown): “For more details on VaR, see for instance, Duffie and Pan (1997), Jorion (2001), or McNeil et al.”
Convex risk measures and the dynamics of their penalty functions (2006, background): “This involves the following stability property for the representing set of measures, sometimes called fork convexity as in [9] and multiplicative stabilty or m-stabilty as in [2].”
Risk Measures and Robust Optimization Problems (2006, background): “Delbaen, F.”
Coherent multiperiod risk adjusted values and Bellman’s principle (2007, methodology): “The continuous time case is treated in Delbaen (2001) with stochastic exponentials.”
Time consistent dynamic risk processes (2009, background): “dynamic risk measures have been developed by Delbaen [9] and Artzner et al.”
Dynamic Monetary Risk Measures for Bounded Discrete-Time Processes (2004, background): “…have been studied in different contexts; see, for instance, Koopmans (1960), Kreps and Porteus (1978), Epstein and Zin (1989), Duffie and Epstein (1992), Wang (2003), Epstein and Schneider (2003), Delbaen (2003), Artzner et al. (2004), Riedel (2004), Peng (2004), Roorda et al. (2005), Weber (2005).”
Robust utility maximization in a stochastic factor model (2006, background): “Following Delbaen [7], we see that the martingale D := λD + (1− λ)De η satisfies the SDE dDt = Dt(ξ1t dW 1 t + ξ2t dW 2 t ), where ξt = αtηt + (1− αt)η̃t is at each time a convex combination of η and η̃ with coefficient αt = λD t λD t + (1− λ)D e η t .”
Dynamic risk measures (2010, background): “1 Time consistency Time consistency has been studied extensively in the recent work on dynamic risk measures, see [4, 15, 30, 17, 12, 26, 9, 8, 29, 20, 13, 16] and the references therein.”
Financial markets with volatility uncertainty (2010, result): “Although the measures belonging to the set are mutually singular this result is similar to the classical ambiguity setting when the probability measures inducing the ambiguity are absolutely continuous, see Chen and Epstein (2002), Delbaen (2002). References for the representation theorem for G–expe”